Count comparisons are subjects to many sources of errors which are known in epidemiology as different forms of bias (bias meaning that one does not measure a true value). Such biases can, in general, be categorized as selection bias (due to the way the study subjects are selected), information bias (due to the way the information in the study is obtained), and screening bias (due to the peculiarities of screening for early manifestations of disease, which brings along the possibility of lead-time bias, length-bias, and overdiagnosis).